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Forward Deployed Engineer - US

Updated

$140,000–$160,000New York, NY

Forward Deployed Engineers lead hands-on, end-to-end deployments of Parloa’s enterprise AI platform in complex customer environments.

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View posting at Parloa

At a glance

Posted base pay

$140K–$160KBelow the median

The work

Builds what the customer runs

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales (not covered)
  2. Proof of concept (not covered)
  3. Implementation
  4. Operations
Coding
Writes production code
Builds for
External customers
Level
Senior
Role
Technical lead

What they ask for

Experience

  • 4+ yearsprofessional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact

Background

  • Software engineering
  • Solutions and customer engineering
  • Implementation and data engineering

Tools

  • Python
  • TypeScript
  • Node.js
  • OpenAI
  • Microsoft Azure
  • Kubernetes
  • Docker
  • Terraform
  • Kafka
  • MCP

Less common in FDE jobs

  • Company size: About 201–1,000 people19%
  • Company stage: Later private32%
  • Individual contributor or manager: Technical lead47%

Share of US FDE postings that state each fact.

The job description from Parloa

Posted by Parloa on

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale.

About the role:

As a Forward Deployed Engineer (FDE) at Parloa, you’ll be on the front lines of enterprise AI adoption - delivering cutting-edge technology into some of the most complex environments in the world. Your mission: lead end-to-end deployment projects from an engineering perspective - not just implementing what exists, but engineering what’s required to make it succeed at enterprise scale.

FDEs are our in-field product engineers. You will build what doesn’t yet exist, adapt architecture to enterprise realities, and engineer integrations across systems and APIs to make deployments successful. Your work is hands-on and code-first - you’ll be building, debugging, and engineering solutions directly in the field. What you ship not only makes deployments succeed, it also defines how customers experience Parloa and shapes what our product becomes.

This is not about maintenance. This is about engineering what makes it work in production, under real-world enterprise constraints, at speed and scale

Areas of ownership:

  • Own deployment engineering projects: Lead the technical execution (incl. product engineering) of Parloa’s deployments inside large, complex enterprise environments
  • Design for scale and resilience: Architect deployment solutions that meet enterprise-grade requirements for performance, reliability, and security
  • Engineer solutions where none exist: Build custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements
  • Work across systems & stacks: Operate at the intersection of backend engineering, DevOps, and data engineering to ensure seamless delivery
  • Partner with enterprise teams: Collaborate directly with customer engineering organizations to overcome constraints and deliver measurable outcomes
  • Guide and mentor others: Collaborate with and provide technical guidance to more junior in-field engineers
  • Influence at senior levels: Engage with enterprise architects and senior technical stakeholders, discussing solutions and architectures in depth to ensure alignment and credibility
  • Debug under pressure: Rapidly unblock issues in mission-critical environments and ensure customer success.
  • Shape the product: Act as the feedback loop between the field and our core engineering teams - turning deployment learnings into platform evolution
  • Deliver long-term impact: Work closely with Deployment Strategists to ensure scalable architectures and durable customer value

Our Technology Stack: Python,TypeScript, Node.js, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP

Who you are:

  • 4+ years of professional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact
  • Proven track record of leading deep technical deployments and integrations in large-scale enterprise environments
  • Strong technical depth across backend engineering, infrastructure-as-code, Kubernetes/cloud platforms, APIs, and databases - with proven experience in systems design and the ability to go hands-on in production systems
  • Ability to operate independently in ambiguous, high-responsibility settings, especially when deploying live to enterprise systems
  • A builder’s mindset with bias for action, creativity under pressure, and an obsession with making things work in the real world
  • Degree in Computer Science, Engineering, or related technical field
  • Strong plus: Experience building or integrating AI/LLM-powered systems (e.g., embedding agent workflows, vector databases, prompt orchestration)

Our recruiting process:

TA Screen → Hiring Manager Call → Technical Interview → Bar Raiser

Salary ranges include OTE

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

Salary Range

$140,000—$160,000 USD

Parloa is committed to upholding the highest data protection standards for our clients' and employees' data. All our employees are instrumental in ensuring the utmost care, GDPR, and ISO compliance, including ISO 27001, in handling sensitive information.

Parloa is an e-verify employer in the USA. Please click here to learn more.

* We provide equal opportunities to all qualified applicants regardless race, gender, sexual orientation, age, religion, national origin, disability status, socioeconomic background and other characteristics.

View posting at Parloa

About Parloa

AI Agent Management Platform enabling enterprise customer service at scale; reimagines CX as agentic, multilingual, conversational interactions across voice and chat.

Series D · 200–500 people

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Pay and conditions

Posted pay
$140,000–$160,000
Pay details

Salary Range USD 140000–160000.

Location
New York, NY
Experience requirements
  • 4+ years: professional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact (required)